Applications of chemical fingerprints and machine learning in plant ecology: Recent progress and future perspectives
文献类型: 外文期刊
作者: Zhong, Chen 1 ; Li, Li 2 ; Wang, Yuan-Zhong 1 ;
作者机构: 1.Med Plants Res Inst, Yunnan Acad Agr Sci, Kunming 650200, Peoples R China
2.Jishou Univ, Coll Biol Resources & Environm Sci Hunan Prov, Jishou 416000, Peoples R China
关键词: Chemical fingerprints; Chemometrics; Plant ecology; Analytical techniques; Machine learning algorithms
期刊名称:MICROCHEMICAL JOURNAL ( 影响因子:4.9; 五年影响因子:4.5 )
ISSN: 0026-265X
年卷期: 2024 年 206 卷
页码:
收录情况: SCI
摘要: With the rapid development of chromatography, spectroscopy and other detection techniques, chemical fingerprinting has become a powerful tool for ecology research. The data generated by these techniques contain a large amount of key information related to the molecular structure, and the optimization and study of these data using chemometrics and machine learning algorithms will have higher precision and accuracy. This paper reviews the analytical techniques used to generate chemical fingerprints in recent years and scrutinises the diversity of applications of chemical fingerprints in the field of plant ecology. Applications in combination with machine learning are emphasized. Prospects for chemical fingerprinting combined with machine learning in plant ecology include the development of fingerprinting databases for accurate species identification, and the integration of advanced techniques to incorporate fingerprinting techniques into ecological modelling to predict plant responses to environmental changes. These innovative avenues hold the promise of improving our understanding of plants and their complex interactions in various ecosystems and integrating them to advance ecological research.
- 相关文献
作者其他论文 更多>>
-
Analysis of Chemical Changes during Maturation of Amomum tsao-ko Based on GC-MS, FT-NIR, and FT-MIR
作者:He, Gang;Yang, Shao-bing;Wang, Yuan-zhong;He, Gang
关键词:
-
Suitable habitat prediction and identification of origin of Lanxangia tsao-ko
作者:He, Gang;Yang, Shao-bing;Wang, Yuan-zhong;He, Gang
关键词:Medicinal plant; FT-NIR spectroscopy; Machine learning; Suitable habitats; Origin identification
-
Application of spectral image processing with different dimensions combined with large-screen visualization in the identification of boletes species
作者:Li, Jie-Qing;Liu, Hong-Gao;Wang, Yuan-Zhong;Liu, Hong-Gao
关键词:boletes species; 2DCOS images; 3DCOS images; Alexnet; Resnet; large-screen visualization
-
Traditional uses, chemical compositions and pharmacological activities of Dendrobium: A review
作者:Li, Pei-Yuan;Wang, Yuan-Zhong;Li, Pei-Yuan;Li, Li
关键词:Dendrobium; Traditional use; Chemical composition; Pharmacological activity
-
A rapid identification based on FT-NIR spectroscopies and machine learning for drying temperatures of Amomum tsao-ko
作者:He, Gang;Lin, Qi;Yang, Shao-Bing;Wang, Yuan-Zhong;He, Gang;Lin, Qi
关键词:Identification research; FT-NIR spectroscopies; Machine learning; Chemometrics; Drying temperatures; Amomum tsao-ko
-
The potential of Amomum tsao-ko as a traditional Chinese medicine: Traditional clinical applications, phytochemistry and pharmacological properties
作者:He, Gang;Yang, Shao-bing;Wang, Yuan-zhong;He, Gang
关键词:Amomum tsao-ko; Chinese herbal medicine; Chemical compounds; Physiological characteristics; Review
-
An integrated chemical characterization based on FT-NIR, and GC-MS for the comparative metabolite profiling of 3 species of the genus Amomum
作者:He, Gang;Yang, Shao-bing;Wang, Yuan-zhong;He, Gang
关键词:Genus Amomum; Quality markers; Identification research; Network pharmacology; Deep learning